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» An Improved Random Neighborhood Graph Approach
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GBRPR
2007
Springer
15 years 1 months ago
Constellations and the Unsupervised Learning of Graphs
Abstract. In this paper, we propose a novel method for the unsupervised clustering of graphs in the context of the constellation approach to object recognition. Such method is an E...
Boyan Bonev, Francisco Escolano, Miguel Angel Loza...
PAMI
2010
207views more  PAMI 2010»
14 years 4 months ago
Document Ink Bleed-Through Removal with Two Hidden Markov Random Fields and a Single Observation Field
We present a new method for blind document bleed through removal based on separate Markov Random Field (MRF) regularization for the recto and for the verso side, where separate pri...
Christian Wolf
ICALP
2011
Springer
14 years 1 months ago
Vertex Cover in Graphs with Locally Few Colors
In [13], Erd˝os et al. defined the local chromatic number of a graph as the minimum number of colors that must appear within distance 1 of a vertex. For any ∆ ≥ 2, there are ...
Fabian Kuhn, Monaldo Mastrolilli
157
Voted
PAMI
2010
215views more  PAMI 2010»
14 years 8 months ago
Fusion Moves for Markov Random Field Optimization
—The efficient application of graph cuts to Markov Random Fields (MRFs) with multiple discrete or continuous labels remains an open question. In this paper, we demonstrate one p...
Victor S. Lempitsky, Carsten Rother, Stefan Roth, ...
CORR
2012
Springer
272views Education» more  CORR 2012»
13 years 5 months ago
Fast and Exact Top-k Search for Random Walk with Restart
Graphs are fundamental data structures and have been employed for centuries to model real-world systems and phenomena. Random walk with restart (RWR) provides a good proximity sco...
Yasuhiro Fujiwara, Makoto Nakatsuji, Makoto Onizuk...